subsubsection3-4plus-4minus-4-1.5em plus-0.22em minus-0.1emCompared Methods 
We compare the proposed method with a number of encoder-decoder image captioning models. ShowTell [1]}: The neural image captioner consists of CNN image encoder and LSTM language decoder. Adaptive [2]}: The CNN-LSTM captioner with the adaptive visual attention. Att2in and Att2all: Variants of attention-based models trained with self-critical sequence training (SCST) from [3]}. UpDown: state-of-the-art captioning model with carefully engineered bottom-up and top-down attention [4]}.
In addition, in the following comparison tables and figures, suffix MT indicates that the model has Modality Transition Module embedded, and suffix RL indicates that the model is fine-tuned by reinforcement learning objectives from the SCST [3]}.
